{"id":"W4404773648","doi":"10.1017/cts.2024.664","title":"The role of information science within the clinical translational science ecosystem","year":2024,"lang":"en","type":"review","venue":"Journal of Clinical and Translational Science","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"National Center for Advancing Translational Sciences; National Institutes of Health; National Institute of General Medical Sciences; Northwestern University","keywords":"Translational science; Ecosystem; Data science; Environmental resource management; Environmental science; Computer science; Sociology; Ecology; Biology; Social science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01301801,0.0006960502,0.001181879,0.004636381,0.002039643,0.01216693,0.00168832,0.00582529,0.003433387],"category_scores_gemma":[0.009736951,0.0004448351,0.0007973664,0.006502544,0.008945658,0.01339449,0.006224076,0.009529262,0.001676819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007833487,"about_ca_system_score_gemma":0.02542674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00695281,"about_ca_topic_score_gemma":0.008224332,"domain_scores_codex":[0.9935456,0.00370347,0.0003890565,0.0003808532,0.001420257,0.0005607523],"domain_scores_gemma":[0.9853665,0.01031061,0.0006931691,0.0004507007,0.001749023,0.001429976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000573933,0.00006985413,0.0003706726,0.01460347,0.000126804,0.0003202976,0.002000113,0.0003499219,0.00034401,0.2005607,0.06871071,0.712486],"study_design_scores_gemma":[0.00001138326,0.00003887577,0.0003974625,0.009971698,0.00004290576,0.0003819476,0.0007382713,0.00005530275,0.0001032163,0.02686199,0.9613722,0.00002474764],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001029192,0.9789501,0.0004562039,0.01585991,0.0008015925,0.00001069072,0.000008879127,0.00001635425,0.003793302],"genre_scores_gemma":[0.003869084,0.9816343,0.001191204,0.0108642,0.001405151,0.00002972285,0.0000183541,0.00001114416,0.0009768504],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9878331,"threshold_uncertainty_score":0.06884664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07212902340276299,"score_gpt":0.4416171790109013,"score_spread":0.3694881556081382,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}